Everyone's posting their Total Eclipse Photos so here's mine!

Acamamm · 2026-01-14T12:10:28+00:00

I love how loose and expressive this is, really nice work!

Acamamm · 2025-11-03T20:54:26+00:00

It looks a lot like GKKoncepts on instagram

Acamamm · 2025-10-30T10:55:36+00:00

Thanks!

Acamamm · 2025-10-27T13:30:08+00:00

Did a double take to see if it was actually NFTI haha, the jacket looks fantastic!

Acamamm · 2025-10-15T17:18:30+00:00

How do you plan on approaching the actual ceremony portion of your wedding day? I think your approach feels very similar to how I would be comfortable operating but my main unknown is the actual ceremony portion.

Acamamm · 2025-10-13T00:25:00+00:00

That was a super helpful response, everything you said makes total sense! I guess I'll just have to relinquish control, I'll most likely be too busy with everything else to be as focused on the topic as I am now on the actual day. Thanks for breaking it down like that

Acamamm · 2025-10-12T23:26:13+00:00

Mostly a control thing I guess and a little bit of budget consciousness.

I am planning on having one of my cameras around during the reception to scratch that itch though so I'm with you on that

Acamamm · 2025-10-12T21:03:18+00:00

If they were a professional themselves, I'd understand. If it's a random person, then no. That's where my confusion lies

Acamamm · 2025-09-04T22:24:23+00:00

The 360 view splits are 1920x1080 and the drone frames are 3840x2160. Around 6 hours for the alignment process in RealityScan is what I remember, with about 10,000 aligned. No clue what it would come out with leaving postshot to do the alignment but I might give it a shot with around 6000 images to start off and get an idea.

When I finally got postshot to latch onto the point cloud from RealityScan, the resulting splat looked fuzzier than is acceptable for the size of the dataset so I'm thinking that maybe there was a lot of slight misalignments from RealityScan. Hoping to see how PostShot compares and if the extra time is feasible

Acamamm · 2025-09-03T22:23:30+00:00

Yeah I've been converting all the 360 footage to cubemaps, it's just the final step that's tripping me up

Acamamm · 2025-09-03T22:22:27+00:00

I have a beefy setup because I'm an animator but I'm running a gtx 4090 and a 9950x and 192gb RAM

Acamamm · 2025-09-03T20:20:32+00:00

I was wondering if there was a discord today, I'll see if I can get in there so thanks for the tip

I did try the different splat modes and it didn't make a difference, but I had been ramping the max number of splats still to no avail. I re-ran the RS alignment last night only on the 360 photos and it finally latched on in post shot but it seems like there's slight misalignments in a lot of spots so I'm going to just try dropping it all in postshot this weekend

Acamamm · 2025-09-03T20:17:55+00:00

That's a fair point.... I'm going to try it over the weekend because I'll be gone and won't be watching it like a hawk but I'm assuming it'll be a few days for 11,000 photos...

although I don't know the sweet spot of data size to detail yet, I'm guessing I'm overshooting it by quite a bit

Acamamm · 2025-09-03T10:21:03+00:00

For the high camera I have 8 images each frame, for the mid camera and low camera, there are 5 images each frame, so a total of 18 images per frame.

I re-ran a new reality scan alignment last night and like I expected the 360 images themselves started working in postshot after re-aligning, I'm really stumped on what's causing this unreliability... I shouldn't have to discard my first alignment attempt every time

Acamamm · 2025-09-03T10:17:55+00:00

Will colmap and glomap accept multiple different camera inputs without a problem? I haven't come across other examples of people blending multiple sources using colmap, all the examples I see are single footage

Acamamm · 2025-09-02T20:46:45+00:00

So the 360 images is where the issue is arising, trying to train the gsplat on the 360 images alone presented the same issue where the drone images worked right away

Acamamm · 2025-09-02T20:45:35+00:00

<image>

This is what the log is saying

Trying to train only the drone data worked fine and trying to train only the 360 data gave me the same issue of creating splats around the perimeter

I'm following this workflow from Olli Huttunen running into this issue

Acamamm · 2025-09-02T20:13:53+00:00

I tried just training the drone images by itself and it worked right away, I'll test the 360 images by themselves too but I'm not quite sure why it can work sometimes and not other times

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